Automation and optimization of engineering design team selection considering personality types and course-specific constraints

Abstract

Optimal team selection in introductory and capstone mechanical design courses is vital to the success of the project, and, as such, many studies have been conducted to determine the means of generating ideal design teams. This work seeks to employ multiple areas of design team theory, including the use of Myers-Briggs Type Indicators (MBTI) for personality assessment and the capability for students to be placed in teams with respect to certain course-specific constraints, including project preference and teaming constraints, in order to automate the optimization of design team selection. Various test cases are shown that indicate the weighted multi-objective Mixed-Integer Linear Programming approach can quickly select optimal design teams consisting of diverse personality types, and can also assign students to preferred projects. This work serves as the first step toward a downloadable design team selection software package that will be made freely available to design researchers and educators.